Shifting Storage Regimes and Declining Streamflow Resilience in Mountain Systems

Mountain snow is a globally important source of water for downstream users and ecosystem sustainability, but it is uncertain when and where traditional snow metrics alone provide reliable indicators of water supply. Here, we synthesize large-sample regional analysis with a high-resolution integrated hydrologic model of a headwater basin of the Colorado River (East River, Colorado, 750 km²) to demonstrate the tight coupling between land surface and subsurface process on mountain streamflow generation. Our analysis of nearly 4,700 western US mountain watersheds indicates that streamflow predictability depends not only on snow accumulation magnitude, but on whether snow represents the dominant water reservoir. Snow storage-dominated mountain basins exhibit a tight coupling between peak snow water equivalent and runoff, while mixed storage systems, such as the East River, depend on interactions among snow, rainfall, and groundwater. Recent declines in runoff efficiency and the degradation of low-flow metrics in the East River coincide with persistent subsurface storage deficits due to overlapping climate extremes, signaling a shift toward subsurface storage-limited behavior.  Modeled scenarios of persistent and prolonged warming indicate enhanced vegetation water use reduces recharge, drives substantial groundwater storage loss that disproportionately affects dry years and limits recovery even during wet periods, ultimately reducing annual flows and increasing stream intermittency. Sensitivity experiments further show that the depth and porosity of active bedrock circulation strongly modulate drought response. Deeper, higher-porosity groundwater systems are able to buffer low flows during multi-year drought conditions but experience prolonged post-drought recovery. Collectively, these findings highlight the tight coupling among climate, vegetation, snow, and groundwater, and demonstrate that explicit representation of subsurface storage dynamics is essential for forecasting mountain water supply, ecosystem vulnerability, and drought response under future climate conditions.